Energy Balance in Clusters of Galaxies. Patrick M. Motl & Jack O. Burns Center for Astrophysics and Space Astronomy University of Colorado at Boulder

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1 Energy Balance in Clusters of Galaxies Patrick M. Motl & Jack O. Burns Center for Astrophysics and Space Astronomy University of Colorado at Boulder X-ray and Radio Connections, February 6th, 2004

2 With thanks to: For development and support of the numerical code, enzo. The code is currently available to friendly users. Information available at For a grant of time on NCSA supercomputing facilities and valuable support.

3 Statement of the Problem: Need a predictive, numerical model for clusters of galaxies. This means simulating clusters in a cosmological setting but also need input physics for radiative cooling, star formation, feedback from supernova and active galactic nuclei, thermal conduction - everything that can significantly impact energy balance in the gas.

4 Energy Balance in Clusters of Galaxies Look at the big things, rich clusters of galaxies but keep in mind that scales will change for poor clusters down to groups Measure energy relative to the gravitational potential energy of the cluster, W ~ ergs Measure time in units of the cluster dynamical time, t dyn ~ 1 Gyr

5 Major Mergers For merger of two, equal mass clusters free-falling into one another expect the cluster to thermalize the kinetic energy of the impact, up to ~ 0.1 W emission-weighted temperature X-ray surface brightness

6 Radiative Cooling For L X ~ erg s -1, over t dyn, loose ~ 10-3 W Not a global loss, however, effective on the scale of the core only emission-weighted temperature X-ray surface brightness

7 Star Formation and Supernova Feedback In runs with star formation and supernova feedback, we find a realistic fraction of baryons in stars for thermal feedback of ~ 0.5 kev per particle in the clusters Assume the star formation rate to be uniform in time and supernova feedback provides ~ 10-4 W of energy over t dyn emission-weighted temperature X-ray surface brightness

8 Thermal Conduction (de / dt) conduction = - 4 π r 2 κ eff (dt / dr) erg s -1 κ eff = f κ Spitzer where f ~ 0.3 (Narayan & Medvedev 2001) For our simulated clusters with cooling only find (de / dt) ~ erg s -1 in the core region for f = 0.1. Over t dyn conduction contributes ~ W caveats: magnetic fields preserve cold fronts and small scale temperature structure if κ eff is too high, heat the surrounding intracluster medium (Loeb 2003)

9 Feedback from Active Galactic Nuclei From Omma, Binney, Bryan & Slyz (2003) From published observations of bubble clusters estimate the mechanical work to be ~ ergs For a cycle time of ~ 0.1 Gyr, roughly expect that AGN can contribute energy at the level of W over t dyn Most effective in the cluster core. Consistent with balancing cooling in cluster cores (Ruszkowski & Begelman 2002)

10 Scorecard Structure formation, up to ~ 0.1 W Radiative Cooling (loss of) ~ 10-3 W Supernova Feedback ~ 10-4 W Thermal Conduction ~ W Active Galactic Nuclei Feedback ~ W

11 Adaptive Mesh Refinement (AMR) Simulations of Cluster Formation and Evolution 5 Mpc 36 Mpc ΛCDM Cosmology with Ω m = 0.3, Ω b = 0.026, Ω Λ = 0.7, and σ 8 = Hydro + N-body code uses AMR to achieve high resolution ( to 1 kpc) in dense regions Simulation volume is 256 Mpc on a side, use 7 to 11 levels of refinement within cluster subvolumes Current generation of simulations includes both radiative cooling and star formation with supernova feedback using the Cen & Ostriker (1992) model Archive of numerical clusters with analysis tools available through the Simulated Cluster Archive

12 X Y X Y z = 0.5 z = 0.25 Z Z X Z Y z = 0 Simulation Information 10 levels of refinement (2 kpc) Radiative cooling Star formation and feedback R 200 = 2.6 Mpc M 200 = 2.1 x M solar M dm = 2.0 x M solar M gas = 1.0 x M solar M stars = 2.0 x M solar

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15 A Note of Caution, clusters are not very spherical!

16 Clusters are dynamical... Simultaneous β model fit of Compton parameter, y, and X-ray surface brightness, S X y = y 0 (1 + (θ / θ c ) 2 ) 1/2-3β/2 S X = S X0 (1 + (θ / θ c ) 2 ) 1/2-3β

17 An Additional Argument for AGN feedback Ponman, Sanderson & Finoguenov (2003); entropy = S = T / n e 2/3

18 Ponman et al. Adiabatic Sample Star Formation + Feedback Sample

19 Constraints from testbed clusters Dynamically relaxed systems, no recent mergers to reset the clock No sign of AGN outbursts Yet, has canonical thermal properties in the cluster core Chandra ACIS-I observation of the poor cluster of galaxies, AWM7

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21 Conclusions Energy balance in clusters requires the interplay of several coupled mechanisms Thermal conduction comparable in magnitude to radiative cooling AGN feedback is likely important in cluster cores Clusters are inherently dynamic, geometrically complex systems Major mergers can significantly boost observational signatures (e.g., factor of ~ 10 in the thermal Sunyaev-Zeldovich effect) for short periods (<~ 1 Gyr) Need to observe clusters without X-ray bubbles where astrophysical mechanisms can be isolated